Articles | Volume 12, issue 2
https://doi.org/10.5194/gmd-12-613-2019
https://doi.org/10.5194/gmd-12-613-2019
Methods for assessment of models
 | 
07 Feb 2019
Methods for assessment of models |  | 07 Feb 2019

Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets

Grzegorz Muszynski, Karthik Kashinath, Vitaliy Kurlin, Michael Wehner, and Prabhat

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Cited articles

AMS: Atmospheric River, Glossary of Meteorology, available at: http://glossary.ametsoc.org/wiki/Atmosphericriver, last access: 10 January 2018. a
Burges, C. J.: A tutorial on support vector machines for pattern recognition, Data Min. Knowl. Disc., 2, 121–167, 1998. a
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Short summary
We present the automated method for recognizing atmospheric rivers in climate data, i.e., climate model output and reanalysis product. The method is based on topological data analysis and machine learning, both of which are powerful tools that the climate science community often does not use. An advantage of the proposed method is that it is free of selection of subjective threshold conditions on a physical variable. This method is also suitable for rapidly analyzing large amounts of data.